Towards the estimation of Space Weather-related corrosion on pipelines
Bibliographic record
Abstract
Geomagnetically induced currents (GIC), increased during space weather events, are able to interfere with pipeline corrosion protections systems and potentially can increase corrosion of the pipeline steel. Methods, widely used for the evaluation of annual corrosion rates, are based on exposure of steel to constant currents and voltages (DC), or alternating currents and voltages of a constant frequency (50 Hz or 60 Hz), while GIC are characterised by a continuous frequency spectrum, with the range of frequencies from 10-5 Hz to 1 Hz. This paper introduces the methods for use in the estimation of corrosion rates on pipeline steel produced by GIC (commonly referred to as “telluric currents” in the pipeline industry) and provides results calculated for specific time periods with use of available recordings made on pipelines at the times of geomagnetic storms. As well, annual cumulative corrosion rates are estimated based on the modelling of pipeline currents and voltages. In addition to the detailed presentation of the methods utilised, a comparison of corrosion rates produced by telluric variations on non-protected and protected pipelines located in mid- and high-latitudes is presented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".